Intelligent reports for group decision support systems

The topic of Group Decision Support Systems (GDSS) is a not a recent one. In fact, it has been studied for the last three decades. In this work, we deal with the topic of Intelligent Reports in GDSS’ context. A defective interaction between the system and the decision-maker may lead to the complete failure of the GDSS. However, the study on how and which kind of information should be exposed to decision-makers is almost non-existent. Therefore, it is important to create reports adapted to the specific necessities of each decision-maker so that each one can acknowledge the advantage to use the system and feel motivated to do so. We believe that in this work, we approach important points that require special attention when developing Intelligent Reports. We navigate through all the important factors that affect decision-makers while making a decision. We detail each point and link them to all related questions and to which kind of structure an Intelligent Report should have in order to not compromise the success of the GDSS.This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT - Portuguese Foundation for Science and Technology within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio

A SOA web-based group decision support system considering affective aspects

The topic of Group Decision Support Systems (GDSS) has been studied over the last decades. Supporting decision-makers that participate in group decision-making processes is a complex task, especially when decision-makers have no opportunity to gather at the same place and at the same time. In this work, we propose a Web based Group Decision Support System (WebGDSS) which intends to support decision-makers anywhere, anytime and through almost any kind of devices. Our system was developed under a SOA architecture and we used a multi criteria algorithm that features decision-makers’ cognitive aspects, as well as a component of generation of intelligent reports to feedback the results of decision-making processes to the decision-makers.This work was supported by GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) with the João Carneiro Ph.D. Grant with the Reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio

Generation of intelligent reports for ubiquitous group decision support systems

Supporting group decision-making is a complex process, especially when decision-makers have no opportunity to gather at the same place and at the same time. Besides that, finding solutions may be difficult in case agents representing decision-makers are not able to understand the process and support them accordingly. In this work we present some topics of information that can be reported to decision-makers to improve their perception about the negotiation process. We classified those topics according to two dimensions and we defined an algorithm to select which information will be built for each report.This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT - Portuguese Foundation for Science and Technology within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio

A web-based group decision support system for multicriteria problems

One of the most important factors to determine the success of an organization is the quality of decisions made. Supporting a decision-making process is a complex task, mainly when decision-makers are dispersed. Group decision support systems (GDSSs) have been studied over the last decades with the goal of providing support to decision-makers; however, their acceptance by organizations has been difficult. This happens mostly due to usability problems, loss of interaction between decision-makers, and consequently, loss of information. In this work, we present a web-based GDSS developed to support groups of decision-makers, regardless of their geographic location. The system allows the creation of multicriteria problems and the configuration of the preferences, intentions, and interests of each decision-maker. The presented system uses a multiagent system to combine and process this information, using virtual agents that represent each decision-maker. We believe that, with this approach, we will proceed in the refinements of a successful GDSS to correctly support decision-makers while preserving the valuable intelligence and knowledge that can be generated in face-to-face meetings. Furthermore, the high level of usability that the system provides will contribute to an easier acceptance and adoption of this kind of systems.This work was supported by by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) with GrouPlanner Project (POCI-01-0145-FEDER29178) and within the Projects UID/CEC/00319/2019 and UID/EEA/00760/2019, and the Luís Conceição Ph.D. Grant with the reference SFRH/BD/137150/2018

Sistema de Apoio à tomada de Decisão em Grupo baseado na Web que considera aspetos cognitivos

A tomada de decisão é um processo cognitivo que consiste na seleção de uma ou mais alternativas para solucionar um determinado problema. O atual contexto macroeconómico em que se inserem a maioria das organizações, assim como a forma como estas estão estruturadas, implica que grande parte das decisões sejam tomadas em grupo. Tradicionalmente, estes processos implicam que os intervenientes tenham a necessidade de se encontrarem num mesmo local ao mesmo tempo. Para suportar os processos de tomada de decisão em grupo neste contexto, têm sido estudados os Sistemas de Apoio à Decisão em Grupo baseados na web (SADGWeb). Estes sistemas utilizam mecanismos capazes de proporem uma ou mais alternativas para um determinado problema tendo em conta as preferências dos decisores epermitem a participação em processos de decisão em grupo em qualquer altura e em qualquer lugar. No entanto, os SADGWeb existentes apresentam várias limitações relacionadas com: a interação entre os decisores, a representação das preferências, objetivos e intenções dos decisores e à necessidade de configurações demasiado complexas e morosas. O trabalho descrito nesta dissertação teve como objetivo colmatar algumas das referidas falhas através de uma abordagem que permitisse suportar grupos (com elementos geograficamente dispersos) tirando proveito dos benefícios associados à decisão em grupo cara-a-cara. Para atingir este objetivo foi estudado se: (1) considerar aspetos cognitivos num algoritmo multi-critério permite alcançar decisões mais satisfatórias; (2) é possível gerar relatórios inteligentes que se adaptem às necessidades de cada decisor. Para alcançar o objetivo definido foi desenvolvido um SADGweb especificamente desenhado para lidar com problemas multi-critério e com grupos dispersos. Com o intuito de ultrapassar alguns dos problemas associados à dificuldade de os decisores expressarem as suas preferências, objetivos e intenções, e às complexas e morosas con gurações, foi formulado um método multi-critério que considera aspetos cognitivos. O algoritmo multi-critério desenvolvido considera, para além das preferências dos decisores sobre as alternativas e critérios, o estilo de comportamento que o utilizador selecionar para o processo, o seu nível de expertise em relação ao tópico da decisão e ainda a avaliação que cada decisor faz da credibilidade de cada um dos outros decisores relativamente ao tópico da decisão. Além disto, foram ainda propostos aquilo que se designou de relatórios inteligentes para ultrapassar algumas das limitações inerentes à impossibilidade de interação dos decisores através da forma como a informação sobre o processo é reportada aos decisores. Para isso, foi proposto um algoritmo que permite que os relatórios apresentem a informação aos decisores de acordo com: a disponibilidade que decisor tem para dedicar ao processo e o seu estilo de comportamento. Os resultados obtidos nas experiências realizadas permitiram concluir que o método multicritério proposto permite obter decisões de maior qualidade quando comparado com outros métodos existentes. Em relação aos relatórios inteligentes foi desenvolvida uma metodologia que permite a personalização dos mesmos de acordo com os interesses de cada decisor.Decision-making is a cognitive process that consists of selecting one or more alternatives to solve a given problem. The current macroeconomic context of most organizations, as well as the way they are structured, implies that most decisions are taken in groups. Traditionally, these processes imply that the actors need to be in the same place at the same time. To support group decision-making processes in this context, web-based Group Decision Support Systems (WebGDSS) have been studied. These systems use mechanisms capable of proposing one or more alternatives to a given problem taking into account the preferences of decision makers and allow participation in group decision making anytime, anywhere. However, existing webGDSS present several limitations related to: interaction between decision akers, representation of preferences, goals and intentions of decision makers, and the need for overly complex and time-consuming con gurations. The work described in this dissertation was aimed at ful ll some of these failures through na approach that allowed groups (with geographically dispersed elements) to take advantage of the bene ts associated with face-to-face group decision making. To achieve this goal, we have studied whether: (1) considering cognitive aspects in a multi-criteria algorithm allows us to reach more satisfactory decisions; (2) it is possible to generate intelligent reports that are adapted to the needs of each decision maker. To achieve the de ned objective, a webGDSS speci cally designed to deal with multi-criteria problems and with scattered groups was developed. In order to overcome some of the problems associated with the di culty of decision-makers express their preferences, goals and intentions, and the complex and time-consuming con gurations, a multi-criteria method was formulated that considers cognitive aspects. The multi-criteria algorithm developed considers, in addition to the preferences of the decision makers on the alternatives and criteria, the style of behavior that the user selects for the process, their level of expertise in relation to the decision topic, and also the evaluation that each decision maker makes the credibility of each of the other decision makers regarding the topic of the decision. In addition, what was called intelligent reporting was proposed to overcome some of the limitations inherent in the inability of decision makers to interact through the way information about the process is reported to decision makers. For this, an algorithm was proposed that allows the reports to present the information to the decision makers according to: the availability that the decision maker has to dedicate to the process and its style of behavior. The results obtained in the realized experiments allowed to conclude that the proposed multi-criterion method allows to obtain decisions of greater quality when compared with other existing methods. In relation to intelligent reports, a methodology was developed that allows to customize them according to the interests of each decision-make

Argumentation dialogues in web-based GDSS: an approach using machine learning techniques

Tese de doutoramento em InformaticsA tomada de decisão está presente no dia a dia de qualquer pessoa, mesmo que muitas vezes ela não tenha consciência disso. As decisões podem estar relacionadas com problemas quotidianos, ou podem estar relacionadas com questões mais complexas, como é o caso das questões organizacionais. Normalmente, no contexto organizacional, as decisões são tomadas em grupo. Os Sistemas de Apoio à Decisão em Grupo têm sido estudados ao longo das últimas décadas com o objetivo de melhorar o apoio prestado aos decisores nas mais diversas situações e/ou problemas a resolver. Existem duas abordagens principais à implementação de Sistemas de Apoio à Decisão em Grupo: a abordagem clássica, baseada na agregação matemática das preferências dos diferentes elementos do grupo e as abordagens baseadas na negociação automática (e.g. Teoria dos Jogos, Argumentação, entre outras). Os atuais Sistemas de Apoio à Decisão em Grupo baseados em argumentação podem gerar uma enorme quantidade de dados. O objetivo deste trabalho de investigação é estudar e desenvolver modelos utilizando técnicas de aprendizagem automática para extrair conhecimento dos diálogos argumentativos realizados pelos decisores, mais concretamente, pretende-se criar modelos para analisar, classificar e processar esses dados, potencializando a geração de novo conhecimento que será utilizado tanto por agentes inteligentes, como por decisiores reais. Promovendo desta forma a obtenção de consenso entre os membros do grupo. Com base no estudo da literatura e nos desafios em aberto neste domínio, formulou-se a seguinte hipótese de investigação - É possível usar técnicas de aprendizagem automática para apoiar diálogos argumentativos em Sistemas de Apoio à Decisão em Grupo baseados na web. No âmbito dos trabalhos desenvolvidos, foram aplicados algoritmos de classificação supervisionados a um conjunto de dados contendo argumentos extraídos de debates online, criando um classificador de frases argumentativas que pode classificar automaticamente (A favor/Contra) frases argumentativas trocadas no contexto da tomada de decisão. Foi desenvolvido um modelo de clustering dinâmico para organizar as conversas com base nos argumentos utilizados. Além disso, foi proposto um Sistema de Apoio à Decisão em Grupo baseado na web que possibilita apoiar grupos de decisores independentemente de sua localização geográfica. O sistema permite a criação de problemas multicritério e a configuração das preferências, intenções e interesses de cada decisor. Este sistema de apoio à decisão baseado na web inclui os dashboards de relatórios inteligentes que são gerados através dos resultados dos trabalhos alcançados pelos modelos anteriores já referidos. A concretização de cada um dos objetivos permitiu validar as questões de investigação identificadas e assim responder positivamente à hipótese definida.Decision-making is present in anyone’s daily life, even if they are often unaware of it. Decisions can be related to everyday problems, or they can be related to more complex issues, such as organizational issues. Normally, in the organizational context, decisions are made in groups. Group Decision Support Systems have been studied over the past decades with the aim of improving the support provided to decision-makers in the most diverse situations and/or problems to be solved. There are two main approaches to implementing Group Decision Support Systems: the classical approach, based on the mathematical aggregation of the preferences of the different elements of the group, and the approaches based on automatic negotiation (e.g. Game Theory, Argumentation, among others). Current argumentation-based Group Decision Support Systems can generate an enormous amount of data. The objective of this research work is to study and develop models using automatic learning techniques to extract knowledge from argumentative dialogues carried out by decision-makers, more specifically, it is intended to create models to analyze, classify and process these data, enhancing the generation of new knowledge that will be used both by intelligent agents and by real decision-makers. Promoting in this way the achievement of consensus among the members of the group. Based on the literature study and the open challenges in this domain, the following research hypothesis was formulated - It is possible to use machine learning techniques to support argumentative dialogues in web-based Group Decision Support Systems. As part of the work developed, supervised classification algorithms were applied to a data set containing arguments extracted from online debates, creating an argumentative sentence classifier that can automatically classify (For/Against) argumentative sentences exchanged in the context of decision-making. A dynamic clustering model was developed to organize conversations based on the arguments used. In addition, a web-based Group Decision Support System was proposed that makes it possible to support groups of decision-makers regardless of their geographic location. The system allows the creation of multicriteria problems and the configuration of preferences, intentions, and interests of each decision-maker. This web-based decision support system includes dashboards of intelligent reports that are generated through the results of the work achieved by the previous models already mentioned. The achievement of each objective allowed validation of the identified research questions and thus responded positively to the defined hypothesis.I also thank to Fundação para a Ciência e a Tecnologia, for the Ph.D. grant funding with the reference: SFRH/BD/137150/2018